1B - quantitative research methods

quantitative research … (keywords)

measures and quantifies human experiences

types of relationships between variables that quantitative research allows to be determined

cause-effect relationship , association, covariation

definition of objectivity

the removal of a researcher’s individual biases and perceptions from a research setting

strengths of quantitative research

• greater objectivity

• greater accuracy

• allows for replication and comparative analysis

• ensures reliability and validity

• higher generalisability bc allows for greater sample sizes

limitations of quantitative research

• rigid methodologies limit insight on subjective human experiences

• research settings may be artificial and lack ecological validity

• data collected may be too narrow and represent human psychology too superficially

• statistical data is not completely objective

types of experiments

1. simple experiment — includes two conditions for IV (control and test)

2. field experiment — manipulates the IV the same as above, but conducted in a real-life setting so limits control over EVs

3. quasi-experiment — experimental conditions and groups are based on pre-existing characteristics of participants

4. natural experiments — preexisting IVs that occur naturally (not manipulated by researcher)

characteristics of experiments

• manipulation of IV

• measurement of DV

• control over EVs

• causality (when the above three are added tgt)

• standardised procedure

• research design (independent vs repeated vs matched pair)

• recorded data

• pilot testing (where possible)

what is a field experiment?

a experiment that takes place in a real-life setting.

*still manipulates the IV and measures the DV, but cannot establish causaity due to less control over EVs.

what us a quasi-experiment?

an experiment where participants are grouped based on any number of preexisting characteristics relevant to the hypothesis. (ie: no random allocation)

less control over EVs, so more prone to CVs
*usually conducted in real-life settings

the two main types of quasi-experiments, and what they are

1. non-equivalent groups design - essentially an independent measure experiment without random allocation

2. pretest-posttest design - essentially a repeated measure experiment without random allocation

   *participants complete a pretest > the IV is administered > same participants complete a posttest

what is a natural experiment?

an experiment that uses naturally occurring variables as the IV (therefore the researcher cannot manipulate them)

*useful when subgroups in the population are clearly defined in relation to some variable

**also useful esp when it would be otherwise unethical to stimulate such a variable artificially due to long term harm of participants

definition of a correlation

the mathematical likelihood of a significant relationship exisiting between two variables (shows the extent to which they are related).

reasons to conduct a correlational study over an experiment

1. there is an apparent statistical relationship between variables, but it is not causal.

2. researcher cannot manipulate the IV (for ethical or practical reasons)

3. predicts relationship that can be investigated further using other methods

4. offer predictive validity (verify theories)

5. test concurrent validity (verify a new test/measurement using an old one)

6. test reliability (between methods or researchers)

definition of co-variables

the variables being studied in correlational research

*note: NOT an IV or DV bc both are measured, none are manipulated

definition of a third variable

a variable not considered in a study that may explain the correlation between co-variables

types of correlations and how they are characterised

positive correlation - co-variables that increase together and change in the same direction

negative correlation - co-variables that move in opposite directions (when one increases the other decreases)

definition of the correlational coefficient

a value that indicates the strength of the relationship between co-variables

range of the correlational coefficient

between -1.00 and +1.00

the closer to either pole (-1/+1), the stronger the relationship. the closer to zero, the weaker the relationship